Mobile Big Data

Mobile Big Data
Author: Xiang Cheng,Luoyang Fang,Liuqing Yang,Shuguang Cui
Publsiher: Springer
Total Pages: 125
Release: 2018-08-23
ISBN: 3319961160
Category: Computers
Language: EN, FR, DE, ES & NL

Mobile Big Data Book Excerpt:

This book provides a comprehensive picture of mobile big data starting from data sources to mobile data driven applications. Mobile Big Data comprises two main components: an overview of mobile big data, and the case studies based on real-world data recently collected by one of the largest mobile network carriers in China. In the first component, four areas of mobile big data life cycle are surveyed: data source and collection, transmission, computing platform and applications. In the second component, two case studies are provided, based on the signaling data collected in the cellular core network in terms of subscriber privacy evaluation and demand forecasting for network management. These cases respectively give a vivid demonstration of what mobile big data looks like, and how it can be analyzed and mined to generate useful and meaningful information and knowledge. This book targets researchers, practitioners and professors relevant to this field. Advanced-level students studying computer science and electrical engineering will also be interested in this book as supplemental reading.

Mobile Big Data

Mobile Big Data
Author: Georgios Skourletopoulos,George Mastorakis,Constandinos X. Mavromoustakis,Ciprian Dobre,Evangelos Pallis
Publsiher: Springer
Total Pages: 347
Release: 2017-10-31
ISBN: 3319679252
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Mobile Big Data Book Excerpt:

This book reports on the latest advances in mobile technologies for collecting, storing and processing mobile big data in connection with wireless communications. It presents novel approaches and applications in which mobile big data is being applied from an engineering standpoint and addresses future theoretical and practical challenges related to the big data field from a mobility perspective. Further, it provides an overview of new methodologies designed to take mobile big data to the Cloud, enable the processing of real-time streaming events on-the-move and enhance the integration of resource availability through the ‘Anywhere, Anything, Anytime’ paradigm. By providing both academia and industry researchers and professionals with a timely snapshot of emerging mobile big data-centric systems and highlighting related pitfalls, as well as potential solutions, the book fills an important gap in the literature and fosters the further development in the area of mobile technologies for exploiting mobile big data.

Big Data Computing

Big Data Computing
Author: Vivek Kale
Publsiher: CRC Press
Total Pages: 495
Release: 2016-11-25
ISBN: 1498715346
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Big Data Computing Book Excerpt:

This book unravels the mystery of Big Data computing and its power to transform business operations. The approach it uses will be helpful to any professional who must present a case for realizing Big Data computing solutions or to those who could be involved in a Big Data computing project. It provides a framework that enables business and technical managers to make optimal decisions necessary for the successful migration to Big Data computing environments and applications within their organizations.

From Big Data to Big Profits

From Big Data to Big Profits
Author: Russell Walker
Publsiher: Oxford University Press, USA
Total Pages: 320
Release: 2015-08-03
ISBN: 0199378320
Category: Business & Economics
Language: EN, FR, DE, ES & NL

From Big Data to Big Profits Book Excerpt:

Vast holdings and assessment of consumer data by large companies are not new phenomena. Firms' ability to leverage the data to reach customers in targeted campaigns and gain market share is, and on an unprecedented scale. Major companies have moved from serving as data or inventory storehouses, suppliers, and exchange mechanisms to monetizing their data and expanding the products they offer. Such changes have implications for both firms and consumers in the coming years. In From Big Data to Big Profits, Russell Walker investigates the use of internal Big Data to stimulate innovations for operational effectiveness, and the ways in which external Big Data is developed for gauging, or even prompting, customer buying decisions. Walker examines the nature of Big Data, the novel measures they create for market activity, and the payoffs they can offer from the connectedness of the business and social world. With case studies from Apple, Netflix, Google, and Amazon, Walker both explores the market transformations that are changing perceptions of Big Data, and provides a framework for assessing and evaluating Big Data. Although the world appears to be moving toward a marketplace where consumers will be able to "pull" offers from firms, rather than simply receiving offers, Walker observes that such changes will require careful consideration of legal and unspoken business practices as they affect consumer privacy. Rigorous and meticulous, From Big Data to Big Profits is a valuable resource for graduate students and professionals with an interest in Big Data, digital platforms, and analytics.

The Big Data Driven Digital Economy Artificial and Computational Intelligence

The Big Data Driven Digital Economy  Artificial and Computational Intelligence
Author: Abdalmuttaleb M. A. Musleh Al-Sartawi
Publsiher: Springer Nature
Total Pages: 472
Release: 2021-05-28
ISBN: 3030730573
Category: Computers
Language: EN, FR, DE, ES & NL

The Big Data Driven Digital Economy Artificial and Computational Intelligence Book Excerpt:

This book shows digital economy has become one of the most sought out solutions to sustainable development and economic growth of nations. This book discusses the implications of both artificial intelligence and computational intelligence in the digital economy providing a holistic view on AI education, economics, finance, sustainability, ethics, governance, cybersecurity, blockchain, and knowledge management. Unlike other books, this book brings together two important areas, intelligence systems and big data in the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations. The chapters hereby focus on how societies can take advantage and manage data, as well as the limitations they face due to the complexity of resources in the form of digital data and the intelligence which will support economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, students, economic development strategies, and the efforts made by the UN towards achieving their sustainability goals.

Managerial Perspectives on Intelligent Big Data Analytics

Managerial Perspectives on Intelligent Big Data Analytics
Author: Sun, Zhaohao
Publsiher: IGI Global
Total Pages: 335
Release: 2019-02-22
ISBN: 1522572783
Category: Computers
Language: EN, FR, DE, ES & NL

Managerial Perspectives on Intelligent Big Data Analytics Book Excerpt:

Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.

Signal Processing and Networking for Big Data Applications

Signal Processing and Networking for Big Data Applications
Author: Zhu Han,Mingyi Hong,Dan Wang
Publsiher: Cambridge University Press
Total Pages: 135
Release: 2017-04-27
ISBN: 1108155944
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Signal Processing and Networking for Big Data Applications Book Excerpt:

This unique text helps make sense of big data in engineering applications using tools and techniques from signal processing. It presents fundamental signal processing theories and software implementations, reviews current research trends and challenges, and describes the techniques used for analysis, design and optimization. Readers will learn about key theoretical issues such as data modelling and representation, scalable and low-complexity information processing and optimization, tensor and sublinear algorithms, and deep learning and software architecture, and their application to a wide range of engineering scenarios. Applications discussed in detail include wireless networking, smart grid systems, and sensor networks and cloud computing. This is the ideal text for researchers and practising engineers wanting to solve practical problems involving large amounts of data, and for students looking to grasp the fundamentals of big data analytics.

Data Science and Digital Business

Data Science and Digital Business
Author: Fausto Pedro García Márquez,Benjamin Lev
Publsiher: Springer
Total Pages: 316
Release: 2019-01-04
ISBN: 3319956515
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Data Science and Digital Business Book Excerpt:

This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.

Big Data at Work

Big Data at Work
Author: Scott Tonidandel,Eden B. King,Jose M. Cortina
Publsiher: Routledge
Total Pages: 382
Release: 2015-11-06
ISBN: 1317702700
Category: Psychology
Language: EN, FR, DE, ES & NL

Big Data at Work Book Excerpt:

The amount of data in our world has been exploding, and analyzing large data sets—so called big data—will become a key basis of competition in business. Statisticians and researchers will be updating their analytic approaches, methods and research to meet the demands created by the availability of big data. The goal of this book is to show how advances in data science have the ability to fundamentally influence and improve organizational science and practice. This book is primarily designed for researchers and advanced undergraduate and graduate students in psychology, management and statistics.

Data Driven Innovation Big Data for Growth and Well Being

Data Driven Innovation Big Data for Growth and Well Being
Author: OECD
Publsiher: OECD Publishing
Total Pages: 456
Release: 2015-10-06
ISBN: 9264229353
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Data Driven Innovation Big Data for Growth and Well Being Book Excerpt:

This report improves the evidence base on the role of Data Driven Innovation for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks.

Big Data Processing Using Spark in Cloud

Big Data Processing Using Spark in Cloud
Author: Mamta Mittal,Valentina E. Balas,Lalit Mohan Goyal,Raghvendra Kumar
Publsiher: Springer
Total Pages: 264
Release: 2018-06-16
ISBN: 9811305501
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Processing Using Spark in Cloud Book Excerpt:

The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data’s immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.

Financial And Economic Systems Transformations And New Challenges

Financial And Economic Systems  Transformations And New Challenges
Author: Zied Ftiti,Hachmi Ben Ameur,Wael Louhichi
Publsiher: World Scientific
Total Pages: 608
Release: 2021-03-22
ISBN: 1786349515
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Financial And Economic Systems Transformations And New Challenges Book Excerpt:

In the last twenty years, several periods of turmoil have shaped the financial and economic system. Many regulatory policies, such as Basel III, have been introduced to overcome further crises and scandals. In addition, monetary policy has experienced a transition from conventional to unconventional frameworks in most industrialized and emerging economies. For instance, turning to hedge and diversification of portfolios, commodities markets have attracted increasing interest. More recently, new forms of money have been introduced, such as virtual money. These changes have influenced governance features at both macro and micro levels. Therefore, calls for ethical and sustainable standards in financial and economic spheres have been growing since 2007.Financial and Economic Systems: Transformations and New Challenges provides readers with insights about future transformations and challenges for financial and economic systems. Prominent contributors focus on different aspects, providing a global overview of crisis implications. The book is split into four main areas: Changes in the Real Sphere, covering issues related to yields, risk, unconventional monetary policy, and macroprudential policy; Financial Markets and Macroeconomics, covering uncertainty in finance and economics; CSR, Sustainability and Ethical Finance, highlighting the emergence of corporate social responsibility; and Digitalization, Blockchain and FinTech and the consequences of these transformations on markets and economic systems.

Machine Learning Optimization and Data Science

Machine Learning  Optimization  and Data Science
Author: Giuseppe Nicosia,Panos Pardalos,Giovanni Giuffrida,Renato Umeton,Vincenzo Sciacca
Publsiher: Springer
Total Pages: 562
Release: 2019-02-16
ISBN: 3030137090
Category: Computers
Language: EN, FR, DE, ES & NL

Machine Learning Optimization and Data Science Book Excerpt:

This book constitutes the post-conference proceedings of the 4th International Conference on Machine Learning, Optimization, and Data Science, LOD 2018, held in Volterra, Italy, in September 2018.The 46 full papers presented were carefully reviewed and selected from 126 submissions. The papers cover topics in the field of machine learning, artificial intelligence, reinforcement learning, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications.

Machine Learning and Big Data Analytics Paradigms Analysis Applications and Challenges

Machine Learning and Big Data Analytics Paradigms  Analysis  Applications and Challenges
Author: Aboul Ella Hassanien,Ashraf Darwish
Publsiher: Springer Nature
Total Pages: 648
Release: 2020-12-14
ISBN: 303059338X
Category: Computers
Language: EN, FR, DE, ES & NL

Machine Learning and Big Data Analytics Paradigms Analysis Applications and Challenges Book Excerpt:

This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems
Author: K. Suganthi,R. Karthik,G. Rajesh,Peter Ho Chiung Ching
Publsiher: CRC Press
Total Pages: 296
Release: 2021-09-14
ISBN: 1000441814
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems Book Excerpt:

This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Communication and provides positive and critical discussions on the challenges and prospects. It provides a broad spectrum in understanding the improvements in Machine Learning and Deep Learning that are motivating by the specific constraints posed by wireless networking systems. The book offers an extensive overview on intelligent Wireless Communication systems and its underlying technologies, research challenges, solutions, and case studies. It provides information on intelligent wireless communication systems and its models, algorithms and applications. The book is written as a reference that offers the latest technologies and research results to various industry problems.

Anomaly Detection and Complex Event Processing Over IoT Data Streams

Anomaly Detection and Complex Event Processing Over IoT Data Streams
Author: Patrick Schneider,Fatos Xhafa
Publsiher: Academic Press
Total Pages: 406
Release: 2022-01-21
ISBN: 0128238194
Category: Computers
Language: EN, FR, DE, ES & NL

Anomaly Detection and Complex Event Processing Over IoT Data Streams Book Excerpt:

Anomaly Detection and Complex Event Processing over IoT Data Streams: With Application to eHealth and Patient Data Monitoring presents advanced processing techniques for IoT data streams and the anomaly detection algorithms over them. The book brings new advances and generalized techniques for processing IoT data streams, semantic data enrichment with contextual information at Edge, Fog and Cloud as well as complex event processing in IoT applications. The book comprises fundamental models, concepts and algorithms, architectures and technological solutions as well as their application to eHealth. Case studies, such as the bio-metric signals stream processing are presented –the massive amount of raw ECG signals from the sensors are processed dynamically across the data pipeline and classified with modern machine learning approaches including the Hierarchical Temporal Memory and Deep Learning algorithms. The book discusses adaptive solutions to IoT stream processing that can be extended to different use cases from different fields of eHealth, to enable a complex analysis of patient data in a historical, predictive and even prescriptive application scenarios. The book ends with a discussion on ethics, emerging research trends, issues and challenges of IoT data stream processing. Provides the state-of-the-art in IoT Data Stream Processing, Semantic Data Enrichment, Reasoning and Knowledge Covers extraction (Anomaly Detection) Illustrates new, scalable and reliable processing techniques based on IoT stream technologies Offers applications to new, real-time anomaly detection scenarios in the health domain

Network Security and Communication Engineering

Network Security and Communication Engineering
Author: Kennis Chan
Publsiher: CRC Press
Total Pages: 688
Release: 2015-07-06
ISBN: 1315683555
Category: Computers
Language: EN, FR, DE, ES & NL

Network Security and Communication Engineering Book Excerpt:

The conference on network security and communication engineering is meant to serve as a forum for exchanging new developments and research progresss between scholars, scientists and engineers all over the world and providing a unique opportunity to exchange information, to present the latest results as well as to review the relevant issues on

Green Technology Applications for Enterprise and Academic Innovation

Green Technology Applications for Enterprise and Academic Innovation
Author: Ariwa, Ezendu
Publsiher: IGI Global
Total Pages: 335
Release: 2014-02-28
ISBN: 1466651679
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Green Technology Applications for Enterprise and Academic Innovation Book Excerpt:

In the age of corporate responsibility, green technology and sustainability continue to grip the consciousness of business and academic institutions. However, development of appropriate business-driven green applications requires an awareness of best practices of the green agenda. Green Technology Applications for Enterprise and Academic Innovation addresses the importance of green technology and sustainability for technology, enterprise, and academic innovation in energy management, renewable energy, and carbon reduction strategies. This book acts as the bridge for practitioners, academia, businesses, industrialists, governmental executives, and students seeking research in this emerging area.

Creating Value with Big Data Analytics

Creating Value with Big Data Analytics
Author: Peter C. Verhoef,Edwin Kooge,Natasha Walk
Publsiher: Routledge
Total Pages: 316
Release: 2016-01-08
ISBN: 1317561929
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Creating Value with Big Data Analytics Book Excerpt:

Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics. Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research, and customer relationship management.

Big Data Research for Social Sciences and Social Impact

Big Data Research for Social Sciences and Social Impact
Author: Miltiadis D. Lytras,Anna Visvizi,Kwok Tai Chui
Publsiher: MDPI
Total Pages: 416
Release: 2020-03-19
ISBN: 3039282204
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Big Data Research for Social Sciences and Social Impact Book Excerpt:

A new era of innovation is enabled by the integration of social sciences and information systems research. In this context, the adoption of Big Data and analytics technology brings new insight to the social sciences. It also delivers new, flexible responses to crucial social problems and challenges. We are proud to deliver this edited volume on the social impact of big data research. It is one of the first initiatives worldwide analyzing of the impact of this kind of research on individuals and social issues. The organization of the relevant debate is arranged around three pillars: Section A: Big Data Research for Social Impact: • Big Data and Their Social Impact; • (Smart) Citizens from Data Providers to Decision-Makers; • Towards Sustainable Development of Online Communities; • Sentiment from Online Social Networks; • Big Data for Innovation. Section B. Techniques and Methods for Big Data driven research for Social Sciences and Social Impact: • Opinion Mining on Social Media; • Sentiment Analysis of User Preferences; • Sustainable Urban Communities; • Gender Based Check-In Behavior by Using Social Media Big Data; • Web Data-Mining Techniques; • Semantic Network Analysis of Legacy News Media Perception. Section C. Big Data Research Strategies: • Skill Needs for Early Career Researchers—A Text Mining Approach; • Pattern Recognition through Bibliometric Analysis; • Assessing an Organization’s Readiness to Adopt Big Data; • Machine Learning for Predicting Performance; • Analyzing Online Reviews Using Text Mining; • Context–Problem Network and Quantitative Method of Patent Analysis. Complementary social and technological factors including: • Big Social Networks on Sustainable Economic Development; Business Intelligence.